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Study of Urban Growth Dynamics Using Global Human Settlement Layer Data Set: Uttarakhand, India

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Abstract

Due to remote sensing-derived time-series geospatial data sets of built-up area, settlement typologies are becoming increasingly available in public domain. The present study aims to study the urban growth dynamics in Himalayan state of Uttarakhand, India, for the last four decades, using open and freely available Global Human Settlement Layer data sets. The growth dynamics was analysed based on factors like increase in built-up area, hot spot analysis and settlement typologies. The results indicate a highly skewed and unbalanced pattern of urban growth, especially after the formation of Uttarakhand State in year 2000. Most of the urban growth process is confined to foothill cites, while in the hill towns there is a stagnated urban growth. The study emphasizes the applicability of GHSL data sets in analysing the urban growth process in Indian conditions where time-series geospatial data are often lacking.

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References

  • Balk, D., Leyk, S., Jones, B., Montgomery, M. R., & Clark, A. (2018). Understanding urbanization: A study of census and satellite-derived urban classes in the United States, 1990–2010. PLoS ONE,13(12), e0208487. https://doi.org/10.1371/journal.pone.0208487.

    Google Scholar 

  • Balk, D., Montgomery, M. R., Engin, E., Natalie Lin, N., Elizabeth Major, E., & Jones, B. (2019). Urbanization in India: Population and urban classification grids for 2011. Data. https://doi.org/10.3390/data4010035.

    Google Scholar 

  • Bhat, P. A., ul Shafiq, M., Mir, A. A., & Ahmed, P. (2017). Urban sprawl and its impact on landuse/landcover dynamics of Dehradun City, India. International Journal of Sustainable Built Environment,6(2), 513–521.

    Google Scholar 

  • Census of India. (2001). Office of the Registrar General and Census Commissioner, New Delhi, India. Retrieved June 13, 2019 from https://censusindia.gov.in.

  • Census of India. (2011). Office of the Registrar General and Census Commissioner, New Delhi, India. Retrieved June 13, 2019 from https://censusindia.gov.in.

  • Corbane, C., Pesaresi, M., Politis, P., Florczyk, J., Aneta, Melchiorri M., Freire, S., et al. (2018). The grey-green divide: multi-temporal analysis of greenness across 10,000 urban centres derived from the Global Human Settlement Layer (GHSL). International Journal of Digital Earth. https://doi.org/10.1080/17538947.2018.1530311.

    Google Scholar 

  • Deep, S., & Kushwaha, S. P. S. (2020). Urbanization, urban sprawl and environment in Dehradun. In A. Gupta & N. Dalei (Eds.), Energy, Environment and Globalization. Singapore: Springer.

    Google Scholar 

  • Dijkstra, L., & Poelman, H. (2014). Definition of cities and rural areas: the new degree of urbanisation. Regional working paper WP 01/2014, European Commission Directorate-General for Regional and Urban Policy (DG REGIO).

  • Ehrlich, D., Julea, A. & Pesaresi, M. (2014). Global spatial and temporal analysis of human settlements from Optical Earth Observation: Concepts, procedures, and preliminary results. European Commission, Joint Research Centre, Institute for the Protection and Security of the Citizen, EUR 27513, https://doi.org/10.2788/745756.

  • Florczyk, A. J., Ferri, S., Syrris, V., Kemper, T., Halkia, M., Soille, P., et al. (2016). A new European settlement map from optical remotely sensed data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,9(5), 1978–1992.

    Google Scholar 

  • Gerten, C., Fina, S., & Rusche, K. (2019). The sprawling planet: Simplifying the measurement of global urbanization trends. Frontiers in Environmental Science,7, 140. https://doi.org/10.3389/fenvs.2019.00140.

    Google Scholar 

  • Getis, A., & Ord, J. K. (1996). Local spatial statistics: An overview. In P. Longley & M. Batty (Eds.), Spatial analysis: Modelling in a GIS environment (pp. 261–277). Cambridge, England: GeoInformation International.

    Google Scholar 

  • Hoffmann, E. M., Konerding, V., Nautiyal, S., & Buerkert, A. (2019). Is the push-pull paradigm useful to explain rural-urban migration? A case study in Uttarakhand, India. PLoS ONE,14(4), e0214511. https://doi.org/10.1371/journal.pone.0214511.

    Google Scholar 

  • Maithani, S. (2014). Neural networks-based simulation of land cover scenarios in Doon valley, India. Geocarto International. https://doi.org/10.1080/10106049.2014.927535.

    Google Scholar 

  • Maithani, S., Arora, M., & Jain, R. (2010). An artificial neural network based approach for urban growth zonation in Dehradun City, India. Geocarto International,25(8), 663–681.

    Google Scholar 

  • Pandey, K., Mitra, D., Maithani, S., & Karnatak, H. (2018). Urban growth modelling using cellular automata—Markov (CA-Markov) technique. Journal of Applied Mathematics and Computation,2(5), 178–187.

    Google Scholar 

  • Patra, P., & Kantariya, K. (2014). Science-policy interface for disaster risk management in India: Toward an enabling environment. Current Science,107(1), 39–45.

    Google Scholar 

  • Pesaresi, M., Ehrlich, D., Ferri S., Florczyk, A., Carneiro, M., Sergio, F., Halkia S., Julea, A., Kemper, T., Soille, P., & Syrris, V. (2016a). Operating Procedure for the Production of the Global Human Settlement Layer from Landsat Data of the Epochs 1975, 1990, 2000, and 2014. Publications Office of the European Union. https://doi.org/10.2788/253582.

  • Pesaresi, M., Ehrlich, D., J. Florczyk, A., Freire, S., Julea, A., Kemper, T., & Syrris, V. (2016b). The global human settlement layer from Landsat imagery. In IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 7276–7279). Beijing: IEEE. https://doi.org/10.1109/IGARSS.2016.7730897.

  • Pesaresi, M., Ehrilch, D., Florczyk, A. J., Freire, S., Julea, A., Kemper, T., Soille, P., & Syrris, V (2014a). GHS built-up grid, derived from Landsat, multi temporal (1975, 1990, 2000, 2014). European Commission, Joint Research Centre (JRC) [Dataset]PID: http://data.europa.eu/89h/jrc-ghsl-ghs_built_ldsmt_globe_r2014b.

  • Pesaresi, M., Huadong, G., Blaes, X., Ehrlich, D., Ferri, S., Gueguen, L., et al. (2013). A Global Human Settlement Layer from optical HR/VHR RS data: Concept and first results. Applied Earth Observations and Remote Sensing,6(5), 2102–2131. https://doi.org/10.1109/JSTARS.2013.2271445.

    Google Scholar 

  • Pesaresi, M., Melchiorri M., Siragusa, A., & Kemper, T. (2016c). Atlas of the human planet—mapping human presence on earth with the global human settlement layer. JRC103150. Publications Office of the European Union. Luxembourg: European Commission, DG JRC. https://doi.org/10.2788/582834.

  • Pesaresi M., Michele M., Alice S., & Thomas K. (2016d). Atlas of the human planet 2016. Mapping human presence on earth with the global human settlement layer; EUR 28116 EN; https://doi.org/10.2788/582834.

  • Pesaresi, M., Syrris, V., & Julea, A. (2014b). Benchmarking of the Symbolic Machine Learning classifier with state of the art image classification methods—application to remote sensing imagery. JRC Technical Report EUR 27518 EN, European Commission, Joint Research Centre, Institute for the Protection and Security of the Citizen.

  • Pesaresi, M., Syrris, V., & Julea, A. (2016e). A new method for earth observation data analytics based on symbolic machine learning. Remote Sensing,8(5), 399. https://doi.org/10.3390/rs8050399.

    Google Scholar 

  • Statistical Handbook, Uttarakhand. (2010). Directorate of Economics and Statistics Planning Division, Government of Uttarakhand.

  • Taubenbock, H., Wegmann, M., Roth, A., Mehl, H., & Dech, S. (2009). Urbanization in India—spatiotemporal analysis using remote sensing data. Computers, Environment and Urban Systems,33(3), 179–188.

    Google Scholar 

  • Tiwari, P. C., & Joshi, B. (2015). Climate change and rural outmigration in Himalaya. The Journal of Change and Adaptation_in_Socio-Ecological Systems (CASES),2, 8–25.

    Google Scholar 

  • Tiwari, P., Joshi, B., & Joshi, B. (2018). Urban growth in the Himalayas: Understanding the process and options for sustainable development. Journal of Urban and Regional Studies on Contemporary India,4(2), 15–27.

    Google Scholar 

  • Tran, D. X., Pla, F., Latorre-Carmona, P., Myint, S. W., Caetano, M., & Kieu, H. V. (2017). Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing,124, 119–132. https://doi.org/10.1016/j.isprsjprs.2017.01.001.

    Google Scholar 

  • Walker, B. (2011). Urban peaks in the Himalayas. China Dialogue. Retrieved February 15, 2020, from https://www.chinadialogue.net/article/show/single/en/4306-Urban-peaks-in-the-Himalayas.

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Authors and Affiliations

  1. School of Environment and Natural Resources, Doon University, Dehradun, India

    Garima Nautiyal & Archana Sharma

  2. Urban and Regional Studies Department, Indian Institute of Remote Sensing, Dehradun, India

    Sandeep Maithani

Authors
  1. Garima Nautiyal
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  2. Sandeep Maithani
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  3. Archana Sharma
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Correspondence to Sandeep Maithani.

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Nautiyal, G., Maithani, S. & Sharma, A. Study of Urban Growth Dynamics Using Global Human Settlement Layer Data Set: Uttarakhand, India. J Indian Soc Remote Sens 48, 817–827 (2020). https://doi.org/10.1007/s12524-020-01115-6

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  • DOI: https://doi.org/10.1007/s12524-020-01115-6

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